Technical Field
The present invention relates to performance metrics and, more particularly, to characterizing dynamics of performance across time and social networks using a chain graph.
Description of the Related Art
Measuring performance in a large, multi-actor system can be challenging, such as a large company or a complex process. However, the benefits are substantial. For example, individuals in an organization influence one another through various mechanisms and recognizing poor performance can lead to quickly providing a solution to underlying problems. Similarly, predictions regarding future performance can be made and accounted for.
Left unchecked, poor performance from one actor in the system's structure can affect the performance of others. For example, if one entity or actor is a bottleneck for a given task, poor performance will starve work processes down the chain and prevent them from performing to their potential. Good performance is similarly contagious across the social network graph. For example, particularly good managers will enhance the productivity of everyone working with them. These interconnections provide a means for understanding the operational dynamics of an entire organization.
However, performance metrics are often difficult to apply regularly across an entire organization. There will frequently be gaps in reporting, where one or more people will not provide metrics. The gaps in the data can be substantial, making it difficult to use the metrics to good effect. For example, performance data may be unavailable for a actor in the system. Such cases arise frequently, leaving large holes in the description of the organization.